Combined Optimization of a Recurve Actuator and its Drive Circuit

Abdalla, Mostafa; Song, Chunping; Lindner, Douglas K.; Gürdal, Zafer

doi:10.1177/1045389x03034689

Cited by 3 publications

(9 citation statements)

References 9 publications

(17 reference statements)

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“…It also depends on the matching of the actuator stiffness to the structure stiffness through R. Similar conclusions were found in Abdalla et al (2003) for a structure actuated by a combination of a PZT stack and a compliant mechanism.…”

Section: Energy Analysissupporting

confidence: 69%

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Design of a recurve actuator for maximum energy efficiency

Seresta¹,

Ragon²,

Abdalla³

et al. 2006

Smart Mater. Struct.

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In this paper we study the optimal design of recurve arrays. An analytic model of the static response of the recurve actuator with energy flow in the system is derived. Two optimization problems for the recurve array are formulated with material, packaging, and performance constraints. One formulation is based on minimum weight. The second formulation is based on energy efficiency. A genetic algorithm is used to find the optimum designs. Recurve arrays designed for maximum energy conversion efficiency are compared to those designed for minimum weight. Parametric studies are conducted to investigate the effect of the stiffness of the driven structure and the maximum deliverable voltage on the optimized designs. These optimization formulations are effective design tools for a relatively complex actuator.

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Section: Energy Analysissupporting

confidence: 69%

“…For the recurve geometry as defined in figures 3 and 4, the E I V , μ, and c, are defined in terms of the geometric and material properties of the beam in the following form (Abdalla et al 2003) …”

Section: Modeling Of the Recurve Arraymentioning

confidence: 99%

Design of a recurve actuator for maximum energy efficiency

Seresta¹,

Ragon²,

Abdalla³

et al. 2006

Smart Mater. Struct.

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“…And the last constraint is that the piezoelectric material cannot become saturated. A more detailed description is given in [10].…”

Section: Design Constraintsmentioning

confidence: 99%

“…All these constraints are necessary and enough for this driving amplifier circuit design. The detailed description can be referred to [10].…”

Section: Design Constraintsmentioning

confidence: 99%

“…This causes the beam to bend with positive curvature up to the mid-span and negative curvature over the other half, producing a relative displacement of the ends of the beam in a direction perpendicular to the beam axis without relative rotation of the ends. A comprehensive description of the finite element model of the recurve actuator is given in [10]. The assembled system of equations takes the form,…”

Section: Actuatormentioning

confidence: 99%

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Combined design of recurve actuators and drive electronics for maximum energy efficiency

et al. 2004

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Smart structures typically consist of many interacting components, which result in a closed loop formed by an actuator, structure, sensors, controller, and drive circuit components. Despite the recognition of component interactions, much of the traditional design approach for such systems is highly compartmentalized and sequential. The primary objective of the present work is to develop a basic understanding of the energy flow and dynamic interaction between the electrical and mechanical subsystems of smart actuators. When operating from portable power sources, a crucial factor in determining the performance of such a smart system is the battery capacity required for the actuator to operate through a given time span along with its life time. The real and reactive power in such a system will determine the battery life and size separately. While the real power is dissipated only in the drive circuit, the reactive power of the circuit and the actuator cannot be calculated individually, where the interaction arises. Multi-objective function optimization problem, which combines the real and reactive power by different weights, will result in a better balanced solution than optimizing either one of them separately. Genetic algorithm is applied for discrete component selection to generate more realistic designs. The optimization result is illustrated in the paper, as well as their relationship with multi-objective functions.

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